methods, notes and classification Metropolitan Regions methods, notes and classification

OECD Regional Statistics - Metropolitan Regions

Abstract

In assessing regional competitiveness policies, the OECD Territorial Development Policy Committee and its Working Parties on Territorial Indicators and Urban Policy, are increasingly called to compare the economic and social performances of Metropolitan Regions across member countries.

A Metropolitan Region typically consists of a core area with significant concentration of employment or population and a surrounding area densely populated and closely tied with the core.

Data sources used

The Metropolitan database contains data for 281 metro areas with a population of 500,000 or more over 30 OECD countries. These metro areas follow a harmonized functional definition developed by the OECD, in cooperation with the European Commission.

Further information read the publication:

http://www.oecd.org/regional/redefiningurbananewwaytomeasuremetropolitanareas.htm%5D.%20Additional%20information%20can%20be%20found%20in%20the%20following%20link:%20http://measuringurban.oecd.org/content/The%20OECD%20Metropolitan%20eXplorer.pdf

Reference period

The Regional Database contains annual data from 2000 to the most recent available year.

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* OECD STATISTICS                                                              *
* PARIS                   OECD Regional Statistics: Metropolitan Regions       *
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STRUCTURE OF THE CODE :   XXXXX / XX / XX

SUB-CODES :

    1   XXXXX....   Country/Region (Territorial level 2)
    2   .....XX..   Blank
    3   .......XX   Variable



SUB-CODE  1 : Country/Region (Territorial level 2)
-----------

        AUS   Australia
        AUS01 .Sydney
        AUS02 .Melbourne
        AUS03 .Brisbane
        AUS04 .Perth
        AUS05 .Adelaide
        AUS06 .Gold Coast-Tweed Heads

        AUT   Austria
        AT001 .Vienna
        AT002 .Graz
        AT003 .Linz

        BEL   Belgium
        BE001 .Brussels
        BE002 .Antwerp
        BE003 .Ghent
        BE005 .Liege

        CAN   Canada
        CAN01 .Edmonton
        CAN04 .Calgary
        CAN06 .Winnipeg
        CAN09 .Vancouver
        CAN16 .Quebec
        CAN20 .Montreal
        CAN21 .Ottawa-Gatineau
        CAN26 .Toronto
        CAN29 .Hamilton

        CHE   Switzerland
        CH001 .Zurich
        CH002 .Geneva
        CH003 .Basel

        CHL   Chile
        CL010 .Valparaφso
        CL011 .Santiago
        CL020 .Concepci≤n

        CZE   Czech Republic
        CZ001 .Prague
        CZ002 .Brno
        CZ003 .Ostrava

        DEU   Germany
        DE001 .Berlin
        DE002 .Hamburg
        DE003 .Munich
        DE004 .Cologne
        DE005 .Frankfurt
        DE006 .Essen
        DE007 .Stuttgart
        DE008 .Leipzig
        DE009 .Dresden
        DE010 .Dortmund
        DE011 .Dⁿsseldorf
        DE012 .Bremen
        DE013 .Hanover
        DE014 .Nuremberg
        DE015 .Bochum
        DE027 .Freiburg im Breisgau
        DE033 .Augsburg
        DE034 .Bonn
        DE035 .Karlsruhe
        DE040 .Saarbrⁿcken
        DE501 .Duisburg
        DE502 .Mannheim
        DE504 .Mⁿnster
        DE507 .Aachen

        DNK   Denmark
        DK001 .Copenhagen

        EST   Estonia
        EE001 .Tallinn

        ESP   Spain
        ES001 .Madrid
        ES002 .Barcelona
        ES003 .Valencia
        ES004 .Seville
        ES005 .Zaragoza
        ES006 .Mßlaga
        ES008 .Las Palmas
        ES019 .Bilbao

        FIN   Finland
        FI001 .Helsinki

        FRA   France
        FR001 .Paris
        FR003 .Lyon
        FR004 .Toulouse
        FR006 .Strasbourg
        FR007 .Bordeaux
        FR008 .Nantes
        FR009 .Lille
        FR010 .Montpellier
        FR011 .Saint-╔tienne
        FR013 .Rennes
        FR026 .Grenoble
        FR032 .Toulon
        FR203 .Marseille
        FR205 .Nice
        FR215 .Rouen

        GRC   Greece
        GR001 .Athens
        GR002 .Thessalonica

        HUN   Hungary
        HU001 .Budapest

        IRL   Ireland
        IE001 .Dublin

        ITA   Italy
        IT001 .Rome
        IT002 .Milan
        IT003 .Naples
        IT004 .Turin
        IT005 .Palermo
        IT006 .Genova
        IT007 .Florence
        IT008 .Bari
        IT009 .Bologna
        IT010 .Catania
        IT011 .Venice

        JPN   Japan
        JP003 .Sapporo
        JP013 .Sendai
        JP015 .Niigata
        JP020 .Toyama
        JP021 .Nagano
        JP023 .Kanazawa
        JP024 .Utsunomiya
        JP025 .Maebashi
        JP026 .Mito
        JP030 .Tokyo
        JP031 .Kofu
        JP034 .Nagoya
        JP036 .Numazu
        JP038 .Osaka
        JP039 .Shizuoka
        JP040 .Anjo
        JP042 .Yokkaichi
        JP046 .Himeji
        JP047 .Toyohashi
        JP048 .Hamamatsu
        JP050 .Okayama
        JP051 .Kurashiki
        JP052 .Fukuyama
        JP053 .Hiroshima
        JP054 .Takamatsu
        JP055 .Wakayama
        JP059 .Tokushima
        JP064 .Kitakyushu
        JP065 .Matsuyama
        JP066 .Fukuoka
        JP067 .Kochi
        JP071 .Oita
        JP074 .Kumamoto
        JP075 .Nagasaki
        JP077 .Kagoshima
        JP078 .Naha

        KOR   Korea
        KR004 .Seoul Incheon
        KR015 .Cheongju
        KR018 .Daejeon
        KR022 .Pohang
        KR025 .Daegu
        KR026 .Jeonju
        KR029 .Ulsan
        KR032 .Busan
        KR033 .Changwon
        KR035 .Gwangju

        MEX   Mexico
        MEX01 .Mexicali
        MEX02 .Tijuana
        MEX05 .Jußrez
        MEX08 .Hermosillo
        MEX10 .Chihuahua
        MEX16 .Reynosa
        MEX19 .Monterrey
        MEX20 .Torre≤n
        MEX21 .Saltillo
        MEX22 .Culiacßn
        MEX24 .Durango
        MEX28 .Tampico
        MEX29 .San Luis Potosφ
        MEX31 .Aguascalientes
        MEX33 .Benito Jußrez
        MEX34 .Le≤n
        MEX35 .MΘrida
        MEX37 .Guadalajara
        MEX38 .Irapuato
        MEX40 .QuerΘtaro
        MEX42 .Celaya
        MEX46 .Pachuca de Soto
        MEX50 .Morelia
        MEX51 .Mexico City
        MEX52 .Xalapa
        MEX55 .Toluca
        MEX59 .Veracruz
        MEX60 .Puebla
        MEX61 .Cuernavaca
        MEX70 .Centro
        MEX73 .Oaxaca de Jußrez
        MEX74 .Acapulco de Jußrez
        MEX75 .Tuxtla GutiΘrrez

        NLD   Netherlands
        NL001 .The Hague
        NL002 .Amsterdam
        NL003 .Rotterdam
        NL004 .Utrecht
        NL005 .Eindhoven

        NOR   Norway
        NO001 .Oslo

        POL   Poland
        PL001 .Warsaw
        PL002 .L≤dz
        PL003 .Krak≤w
        PL004 .Wroclaw
        PL005 .Poznan
        PL006 .Gdansk
        PL009 .Lublin
        PL010 .Katowice

        PRT   Portugal
        PT001 .Lisbon
        PT002 .Porto

        SWE   Sweden
        SE001 .Stockholm
        SE002 .Gothenburg
        SE003 .Malm÷

        SVN   Slovenia
        SI001 .Ljubljana

        SVK   Slovak Republic
        SK001 .Bratislava

        GBR   United Kingdom
        UK001 .London
        UK002 .Birmingham (UK)
        UK003 .Leeds
        UK004 .Bradford
        UK005 .Liverpool
        UK006 .Manchester
        UK007 .Cardiff
        UK008 .Sheffield
        UK009 .Bristol
        UK010 .Newcastle
        UK011 .Leicester
        UK017 .Portsmouth
        UK023 .Nottingham
        UK097 .Glasgow
        UK098 .Edinburgh

        USA   United States
        US003 .Seattle
        US012 .Portland
        US014 .Minneapolis
        US033 .Milwaukee
        US035 .Madison
        US038 .Buffalo
        US039 .Grand Rapids
        US044 .Albany
        US045 .Detroit
        US048 .Boston
        US055 .Chicago
        US060 .Providence
        US065 .Toledo (US)
        US069 .Cleveland
        US070 .Des Moines
        US077 .Omaha
        US081 .Akron
        US084 .New York
        US089 .Salt Lake City
        US097 .Pittsburgh
        US103 .Harrisburg
        US106 .Philadelphia
        US107 .Columbus
        US114 .Denver
        US115 .Indianapolis
        US117 .Dayton
        US122 .Baltimore
        US124 .Cincinnati
        US125 .Washington
        US128 .Kansas City
        US133 .Colorado Springs
        US134 .Saint Louis (US)
        US135 .Sacramento/Roseville
        US141 .Louisville
        US146 .San Francisco
        US147 .Wichita
        US149 .Richmond
        US154 .Norfolk-Portsmouth-Chesapeake-Virginia beach
        US155 .Fresno
        US159 .Las Vegas
        US160 .Nashville
        US161 .Tulsa
        US170 .Raleigh
        US174 .Oklahoma city
        US178 .Charlotte
        US180 .Albuquerque
        US181 .Memphis
        US186 .Little Rock
        US190 .Los Angeles
        US195 .Columbia
        US196 .Atlanta
        US202 .Phoenix
        US205 .Birmingham (US)
        US209 .Dallas
        US210 .San Diego
        US212 .Fort Worth
        US213 .Charleston
        US223 .Tucson
        US227 .El Paso
        US233 .Baton Rouge
        US234 .Austin
        US237 .Jacksonville
        US241 .New Orleans
        US242 .Houston
        US245 .San Antonio
        US250 .Orlando
        US251 .Clearwater/Saint Petersburg
        US252 .Tampa
        US259 .Miami
        US261 .Mcallen



SUB-Code  3 : Variable
-----------

       Demographic indicators
           00 Total population of the metropolitan area (persons)
           01 .Population of the city area (persons)
           02 ..Population, City, Youth (0-14)
           03 ..Population, City, Working age (15-64)
           04 ..Populaiton, City, Old (65more)
           05 .Population of the commuting zone area (persons)
           06 ..Population, Commuting Zone, Youth (0-14)
           07 ..Population, Commuting Zone, Working age (15-64)
           08 ..Populaiton, Commuting Zone, Elder (65more)
           09 .Population, Total, Youth (0-14)
           10 .Population, Total, Working age (15-64)
           11 .Populaiton, Total, Old (65more)
           12 .Old-age-dependency ratio
           13 .Youth-dependency ratio
           14 Population of the metropolitan area as a share of national value (%)
           15 .Youth population of the metropolitan area as share of national value (%)
           16 .Working age population of the metropolitan area as a share of national value (%)
           17 .Elderly population of the metropolitan area as a share of national value (%)
           18 .Youth population of the core area as a share of the total metropolitan area youth population (%)
           19 .Working age population of the core area as a share of the total metropolitan area working age population (%)
           20 .Elderly population of the core area as a share of the total metropolitan area elderly population (%)
           21 Population density (persons per km2)
           22 .Population density of the city area (persons per km2)
           23 .Population density of the commuting zone (persons per km2)

       Land cover indicators
           24 Total land area (km2)
           25 .Total land area of the city (km2)
           26 .Total land area of the commuting zone (km2)
           27 Metropolitan land share of national value (%)
           28 .City land share over Metropolitan land area (%)
           29 .Commuting zone land share over Metropolitan land area (%)
           30 Urbanised area (km2)
           31 Urbanised area growth
           32 Urbanised area share (%),,
           33 Green area per million people (square meters per million person),,

       Urban form
           34 Polycentricity
           35 Concentration of population in the core (%)
           36 Sprawl index

       Territorial organisation
           37 Local governments (count)
           38 Local governments in the core (count)
           39 Territorial fragmentation
           40 Average population size of local government

       Economic indicators
           41 GDP (millions US$)
           42 GDP of the metropolitan area as a share of national value (%)
           43 Labour productivity
           44 GDP per capita (US$)

       Income and inequality
           45 Equivalised household disposable income
           46 Gini index
           47 Spatial ordinal entropy index at a 1,000 meters scale

       Environmental indicators
           48 CO2 emissions per capita (tonnes per inhabitant)
           49 .CO2 emissions per capita from transport (tonnes per inhabitant)
           50 .CO2 emissions per capita from energy industry (tonnes per inhabitant)
           51 CO2 emissions of the metropolitan area as a share of national value (%)
           52 .CO2 energy emissions of the metropolitan area as a share of the national energy industry emissions (%)
           53 .CO2 transport emissions of the metropolitan area as a share of the national transport emissions from transport (%)
           54 Estimated average exposure to air pollution (PM2.5) based on imagery data

       Labour indicators
           55 Labour force (persons)
           56 .Labour force of the metropolitan area as a share of national value (%)
           57 Employment (persons)
           58 .Employment of the metropolitan area as a share of national value (%)
           59 Employment as a share of the working age population (%)
           60 Unemployment (persons)
           61 .Unemployment of the metropolitan area as a share of national value (%)
           62 Unemployment as a share of the labour force (%)
           63 Participation rate (%)

       Innovation indicators
           64 PCT patent applications (count)
           65 PCT patent applications of the metropolitan area as % of national value
           66 PCT patents applications per 10,000 inhabitants


Units:
------

Units of measure refer to persons for Population by age and sex,
Labour Force, Employment, Unemployment and Annual Average
Population. Regional surface is expressed in square metres,
while population density refers to persons per square metre.
GDP in current and constant prices is expressed in million of
national currency, while GDP in PPP is expressed in million
of Dollars. Unemployment, Participation and Employment rates
are expressed as percentages. Patents statistics are
expressed as per million population.


    • Demographic indicators
      • 00 Total population of the metropolitan area (persons)
      • 01 .Population of the city area (persons)
      • 02 ..Population, City, Youth (0-14)
      • 03 ..Population, City, Working age (15-64)
      • 04 ..Populaiton, City, Old (65more)
      • 05 .Population of the commuting zone area (persons)
      • 06 ..Population, Commuting Zone, Youth (0-14)
      • 07 ..Population, Commuting Zone, Working age (15-64)
      • 08 ..Populaiton, Commuting Zone, Elder (65more)
      • 09 .Population, Total, Youth (0-14)
      • 10 .Population, Total, Working age (15-64)
      • 11 .Populaiton, Total, Old (65more)
      • 12 .Old-age-dependency ratio
      • 13 .Youth-dependency ratio
      • 14 Population of the metropolitan area as a share of national value (%)
      • 15 .Youth population of the metropolitan area as share of national value (%)
      • 16 .Working age population of the metropolitan area as a share of national value (%)
      • 17 .Elderly population of the metropolitan area as a share of national value (%)
      • 18 .Youth population of the core area as a share of the total metropolitan area youth population (%)
      • 19 .Working age population of the core area as a share of the total metropolitan area working age population (%)
      • 20 .Elderly population of the core area as a share of the total metropolitan area elderly population (%)
      • 21 Population density (persons per km2)
      • 22 .Population density of the city area (persons per km2)
      • 23 .Population density of the commuting zone (persons per km2)
    • Land cover indicators
      • 24 Total land area (km2)
      • 25 .Total land area of the city (km2)
      • 26 .Total land area of the commuting zone (km2)
      • 27 Metropolitan land share of national value (%)
      • 28 .City land share over Metropolitan land area (%)
      • 29 .Commuting zone land share over Metropolitan land area (%)
      • 30 Urbanised area (km2)
      • 31 Urbanised area growth
      • 32 Urbanised area share (%),,
      • 33 Green area per million people (square meters per million person),,
    • Urban form
      • 34 Polycentricity
      • 35 Concentration of population in the core (%)
      • 36 Sprawl index
    • Territorial organisation
      • 37 Local governments (count)
      • 38 Local governments in the core (count)
      • 39 Territorial fragmentation
      • 40 Average population size of local government
    • Economic indicators
      • 41 GDP (millions US$)
      • 42 GDP of the metropolitan area as a share of national value (%)
      • 43 Labour productivity
      • 44 GDP per capita (US$)
    • Income and inequality
      • 45 Equivalised household disposable income
      • 46 Gini index
      • 47 Spatial ordinal entropy index at a 1,000 meters scale
    • Environmental indicators
      • 48 CO2 emissions per capita (tonnes per inhabitant)
      • 49 .CO2 emissions per capita from transport (tonnes per inhabitant)
      • 50 .CO2 emissions per capita from energy industry (tonnes per inhabitant)
      • 51 CO2 emissions of the metropolitan area as a share of national value (%)
      • 52 .CO2 energy emissions of the metropolitan area as a share of the national energy industry emissions (%)
      • 53 .CO2 transport emissions of the metropolitan area as a share of the national transport emissions from transport (%)
      • 54 Estimated average exposure to air pollution (PM2.5) based on imagery data
    • Labour indicators
      • 55 Labour force (persons)
      • 56 .Labour force of the metropolitan area as a share of national value (%)
      • 57 Employment (persons)
      • 58 .Employment of the metropolitan area as a share of national value (%)
      • 59 Employment as a share of the working age population (%)
      • 60 Unemployment (persons)
      • 61 .Unemployment of the metropolitan area as a share of national value (%)
      • 62 Unemployment as a share of the labour force (%)
      • 63 Participation rate (%)
    • Innovation indicators
      • 64 PCT patent applications (count)
      • 65 PCT patent applications of the metropolitan area as % of national value
      • 66 PCT patents applications per 10,000 inhabitants
    • Reporting Country
      • Australia
        • AUS Australia
        • AUS01 .Sydney
        • AUS02 .Melbourne
        • AUS03 .Brisbane
        • AUS04 .Perth
        • AUS05 .Adelaide
        • AUS06 .Gold Coast-Tweed Heads
      • Austria
        • AUT Austria
        • AT001 .Vienna
        • AT002 .Graz
        • AT003 .Linz
      • Belgium
        • BEL Belgium
        • BE001 .Brussels
        • BE002 .Antwerp
        • BE003 .Ghent
        • BE005 .Liege
      • Canada
        • CAN Canada
        • CAN01 .Edmonton
        • CAN04 .Calgary
        • CAN06 .Winnipeg
        • CAN09 .Vancouver
        • CAN16 .Quebec
        • CAN20 .Montreal
        • CAN21 .Ottawa-Gatineau
        • CAN26 .Toronto
        • CAN29 .Hamilton
      • Switzerland
        • CHE Switzerland
        • CH001 .Zurich
        • CH002 .Geneva
        • CH003 .Basel
      • Chile
        • CHL Chile
        • CL010 .Valparaφso
        • CL011 .Santiago
        • CL020 .Concepci≤n
      • Czech Republic
        • CZE Czech Republic
        • CZ001 .Prague
        • CZ002 .Brno
        • CZ003 .Ostrava
      • Germany
        • DEU Germany
        • DE001 .Berlin
        • DE002 .Hamburg
        • DE003 .Munich
        • DE004 .Cologne
        • DE005 .Frankfurt
        • DE006 .Essen
        • DE007 .Stuttgart
        • DE008 .Leipzig
        • DE009 .Dresden
        • DE010 .Dortmund
        • DE011 .Dⁿsseldorf
        • DE012 .Bremen
        • DE013 .Hanover
        • DE014 .Nuremberg
        • DE015 .Bochum
        • DE027 .Freiburg im Breisgau
        • DE033 .Augsburg
        • DE034 .Bonn
        • DE035 .Karlsruhe
        • DE040 .Saarbrⁿcken
        • DE501 .Duisburg
        • DE502 .Mannheim
        • DE504 .Mⁿnster
        • DE507 .Aachen
      • Denmark
        • DNK Denmark
        • DK001 .Copenhagen
      • Estonia
        • EST Estonia
        • EE001 .Tallinn
      • Spain
        • ESP Spain
        • ES001 .Madrid
        • ES002 .Barcelona
        • ES003 .Valencia
        • ES004 .Seville
        • ES005 .Zaragoza
        • ES006 .Mßlaga
        • ES008 .Las Palmas
        • ES019 .Bilbao
      • Finland
        • FIN Finland
        • FI001 .Helsinki
      • France
        • FRA France
        • FR001 .Paris
        • FR003 .Lyon
        • FR004 .Toulouse
        • FR006 .Strasbourg
        • FR007 .Bordeaux
        • FR008 .Nantes
        • FR009 .Lille
        • FR010 .Montpellier
        • FR011 .Saint-╔tienne
        • FR013 .Rennes
        • FR026 .Grenoble
        • FR032 .Toulon
        • FR203 .Marseille
        • FR205 .Nice
        • FR215 .Rouen
      • Greece
        • GRC Greece
        • GR001 .Athens
        • GR002 .Thessalonica
      • Hungary
        • HUN Hungary
        • HU001 .Budapest
      • Ireland
        • IRL Ireland
        • IE001 .Dublin
      • Italy
        • ITA Italy
        • IT001 .Rome
        • IT002 .Milan
        • IT003 .Naples
        • IT004 .Turin
        • IT005 .Palermo
        • IT006 .Genova
        • IT007 .Florence
        • IT008 .Bari
        • IT009 .Bologna
        • IT010 .Catania
        • IT011 .Venice
      • Japan
        • JPN Japan
        • JP003 .Sapporo
        • JP013 .Sendai
        • JP015 .Niigata
        • JP020 .Toyama
        • JP021 .Nagano
        • JP023 .Kanazawa
        • JP024 .Utsunomiya
        • JP025 .Maebashi
        • JP026 .Mito
        • JP030 .Tokyo
        • JP031 .Kofu
        • JP034 .Nagoya
        • JP036 .Numazu
        • JP038 .Osaka
        • JP039 .Shizuoka
        • JP040 .Anjo
        • JP042 .Yokkaichi
        • JP046 .Himeji
        • JP047 .Toyohashi
        • JP048 .Hamamatsu
        • JP050 .Okayama
        • JP051 .Kurashiki
        • JP052 .Fukuyama
        • JP053 .Hiroshima
        • JP054 .Takamatsu
        • JP055 .Wakayama
        • JP059 .Tokushima
        • JP064 .Kitakyushu
        • JP065 .Matsuyama
        • JP066 .Fukuoka
        • JP067 .Kochi
        • JP071 .Oita
        • JP074 .Kumamoto
        • JP075 .Nagasaki
        • JP077 .Kagoshima
        • JP078 .Naha
      • Korea
        • KOR Korea
        • KR004 .Seoul Incheon
        • KR015 .Cheongju
        • KR018 .Daejeon
        • KR022 .Pohang
        • KR025 .Daegu
        • KR026 .Jeonju
        • KR029 .Ulsan
        • KR032 .Busan
        • KR033 .Changwon
        • KR035 .Gwangju
      • Mexico
        • MEX Mexico
        • MEX01 .Mexicali
        • MEX02 .Tijuana
        • MEX05 .Jußrez
        • MEX08 .Hermosillo
        • MEX10 .Chihuahua
        • MEX16 .Reynosa
        • MEX19 .Monterrey
        • MEX20 .Torre≤n
        • MEX21 .Saltillo
        • MEX22 .Culiacßn
        • MEX24 .Durango
        • MEX28 .Tampico
        • MEX29 .San Luis Potosφ
        • MEX31 .Aguascalientes
        • MEX33 .Benito Jußrez
        • MEX34 .Le≤n
        • MEX35 .MΘrida
        • MEX37 .Guadalajara
        • MEX38 .Irapuato
        • MEX40 .QuerΘtaro
        • MEX42 .Celaya
        • MEX46 .Pachuca de Soto
        • MEX50 .Morelia
        • MEX51 .Mexico City
        • MEX52 .Xalapa
        • MEX55 .Toluca
        • MEX59 .Veracruz
        • MEX60 .Puebla
        • MEX61 .Cuernavaca
        • MEX70 .Centro
        • MEX73 .Oaxaca de Jußrez
        • MEX74 .Acapulco de Jußrez
        • MEX75 .Tuxtla GutiΘrrez
      • Netherlands
        • NLD Netherlands
        • NL001 .The Hague
        • NL002 .Amsterdam
        • NL003 .Rotterdam
        • NL004 .Utrecht
        • NL005 .Eindhoven
      • Norway
        • NOR Norway
        • NO001 .Oslo
      • Poland
        • POL Poland
        • PL001 .Warsaw
        • PL002 .L≤dz
        • PL003 .Krak≤w
        • PL004 .Wroclaw
        • PL005 .Poznan
        • PL006 .Gdansk
        • PL009 .Lublin
        • PL010 .Katowice
      • Portugal
        • PRT Portugal
        • PT001 .Lisbon
        • PT002 .Porto
      • Sweden
        • SWE Sweden
        • SE001 .Stockholm
        • SE002 .Gothenburg
        • SE003 .Malm÷
      • Slovenia
        • SVN Slovenia
        • SI001 .Ljubljana
      • Slovak Republic
        • SVK Slovak Republic
        • SK001 .Bratislava
      • United Kingdom
        • GBR United Kingdom
        • UK001 .London
        • UK002 .Birmingham (UK)
        • UK003 .Leeds
        • UK004 .Bradford
        • UK005 .Liverpool
        • UK006 .Manchester
        • UK007 .Cardiff
        • UK008 .Sheffield
        • UK009 .Bristol
        • UK010 .Newcastle
        • UK011 .Leicester
        • UK017 .Portsmouth
        • UK023 .Nottingham
        • UK097 .Glasgow
        • UK098 .Edinburgh
      • United States
        • USA United States
        • US003 .Seattle
        • US012 .Portland
        • US014 .Minneapolis
        • US033 .Milwaukee
        • US035 .Madison
        • US038 .Buffalo
        • US039 .Grand Rapids
        • US044 .Albany
        • US045 .Detroit
        • US048 .Boston
        • US055 .Chicago
        • US060 .Providence
        • US065 .Toledo (US)
        • US069 .Cleveland
        • US070 .Des Moines
        • US077 .Omaha
        • US081 .Akron
        • US084 .New York
        • US089 .Salt Lake City
        • US097 .Pittsburgh
        • US103 .Harrisburg
        • US106 .Philadelphia
        • US107 .Columbus
        • US114 .Denver
        • US115 .Indianapolis
        • US117 .Dayton
        • US122 .Baltimore
        • US124 .Cincinnati
        • US125 .Washington
        • US128 .Kansas City
        • US133 .Colorado Springs
        • US134 .Saint Louis (US)
        • US135 .Sacramento/Roseville
        • US141 .Louisville
        • US146 .San Francisco
        • US147 .Wichita
        • US149 .Richmond
        • US154 .Norfolk-Portsmouth-Chesapeake-Virginia beach
        • US155 .Fresno
        • US159 .Las Vegas
        • US160 .Nashville
        • US161 .Tulsa
        • US170 .Raleigh
        • US174 .Oklahoma city
        • US178 .Charlotte
        • US180 .Albuquerque
        • US181 .Memphis
        • US186 .Little Rock
        • US190 .Los Angeles
        • US195 .Columbia
        • US196 .Atlanta
        • US202 .Phoenix
        • US205 .Birmingham (US)
        • US209 .Dallas
        • US210 .San Diego
        • US212 .Fort Worth
        • US213 .Charleston
        • US223 .Tucson
        • US227 .El Paso
        • US233 .Baton Rouge
        • US234 .Austin
        • US237 .Jacksonville
        • US241 .New Orleans
        • US242 .Houston
        • US245 .San Antonio
        • US250 .Orlando
        • US251 .Clearwater/Saint Petersburg
        • US252 .Tampa
        • US259 .Miami
        • US261 .Mcallen